跳轉到主要內容

Mistral Large 3

MistralMistral開源權重Apache 2.0 · 商用許可

描述

Mistral Large 3 (675B Instruct 2512 Eagle) is a state-of-the-art general-purpose Multimodal granular Mixture-of-Experts model with 41B active parameters and 675B total parameters trained from scratch with 3000 H200s. This model is the base pre-trained version, not fine-tuned for instruction or reasoning tasks, making it ideal for custom post-training processes. Designed for reliability and long-context comprehension - It is engineered for production-grade assistants, retrieval-augmented systems, scientific workloads, and complex enterprise workflows. This model is the Eagle speculator for Mistral Large 3 Instruct. Depending on the task, you can expect noticeable speed-ups on your generations.

發布日期
2025-12-02
參數規模
675.0B
上下文長度
262K
支援模態
image, text

能力雷達圖

34
general
31
coding
43
reasoning
44
science
39
agents
85
multimodal

排行榜排名

領域#排名分數來源
程式碼能力榜323
34.0
AA
通用能力榜324
39.0
AA
科學能力298
45.0
AA

基準測試分數 (LLM Stats)

(LLM Stats (zeroeval))

Biology

GPQANYU + Cohere + Anthropic (2023)43.9%自報

Code

LiveCodeBench34.4%自報

Communication

MM-MT-Bench84.90 / 100自報
Wild Bench68.5%自報

Creativity

Arena Hard55.1%自報

Factuality

SimpleQA23.8%自報

General

MMMLU85.5%自報
MMLU-Redux82.0%自報
TriviaQA74.9%自報

Math

MATH90.4%自報
MATH (CoT)67.6%自報
AMC_2022_2352.0%自報

AA 評測指數

(Artificial Analysis)
Math Index(Artificial Analysis)
38.0
Coding Index(Artificial Analysis)
20.1
Intelligence Index(Artificial Analysis)
15.9
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
0.8
Gpqa(NYU + Cohere + Anthropic (2023))
0.7
Livecodebench(UC Berkeley + MIT + Cornell (2024))
0.5
Aime 25(MAA (Mathematical Association of America))
0.4
Scicode(UIUC + Argonne National Lab (2024))
0.4
Ifbench(Google Research (2023))
0.4
Lcr(Artificial Analysis)
0.3
Tau2(Sierra + U Toronto + Vector Institute (2025))
0.2
Terminalbench Hard(Stanford × Laude Institute (2026))
0.2
Terminalbench V2 1
0.1
Tau Banking
0.1
Hle(Center for AI Safety + Scale AI (2025))
0.0

LLM Stats 分類評分

(LLM Stats (zeroeval))
Language
90
Math
70
Reasoning
50
General
50
Physics
40
Biology
40
Chemistry
40
Code
30
Factuality
20

定價

輸入價格$0.5 / 1M tokens
輸出價格$1.5 / 1M tokens
混合價格(3:1)$0.75 / 1M tokens

速度

Tokens/秒55.8
首Token延遲0.71s
首回答延遲0.71s

供應商價格排行

供應商價格排行

7 個供應商

最便宜: Mistral最貴: 302.AI
供應商輸入輸出
1Mistral主要
$0.5
$1.5
2OpenRouter
$0.5
$1.5
3Kilo Gateway
$0.5
$1.5
4LLM Gateway
$0.5
$1.5
5Pioneer
$0.5
$1.5
6Cortecs
$0.557
$1.671
7302.AI
$1.1
$3.3

比較該模型在不同 API 供應商之間的定價。

外部連結